# Doist/bitmapist

Powerful analytics and cohort library using Redis bitmaps.

Repository: https://github.com/Doist/bitmapist
Canonical: https://ross.abutalabs.com/products/bitmapist
Language: Python
License: BSD-3-Clause
License Family: permissive
Last push: 2026-07-17T19:57:23+00:00

## Health v2 (maintenance only)
Score: 80/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 53, longevity 100
- inputs: {"age_days": 5060, "days_push": 47, "days_rel": 238, "gap_med": 79.5, "n_releases_24m": 5}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1009, forks 77 (observed 2026-08-28T04:03:12.780348+00:00)

## What it is
A Python analytics library that uses Redis bitmaps to track user events at massive scale with minimal memory. It supports real-time queries about user activity and generates cohort retention reports.

## Use cases
- track whether a user has been active today, this week, or this month
- count unique users who performed an action in a time period
- compute user retention percentages across weeks or months
- generate cohort graphs for user retention
- store event data for millions of users in megabytes of memory
- find which users performed a specific action

## When to choose
- you need real-time, highly memory-efficient user activity analytics
- you want cohort and retention reporting backed by Redis
- you need to answer set-based questions (AND/OR) over millions of user events cheaply

## When to avoid
- your user IDs exceed 2^32, which inflates memory usage
- you need complex event schemas or arbitrary attributes per event
- you don't already run Redis or a compatible data store

## Facets
- artifact type: library
- maturity: active
- function: analytics, caching, database-driver
- domain: analytics, databases, data-science
- platform: python
- tags: redis-bitmaps, cohort-analysis, realtime-analytics, user-retention, event-tracking, redis

## Member repositories
- Doist/bitmapist (main) score 80

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:12.780348+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:12:00.280487+00:00, confidence not recorded.
  - readme: https://github.com/Doist/bitmapist (fetched 2026-08-28T04:03:12.780348+00:00, sha bae6623a7652)
  - registry_pypi: https://pypi.org/pypi/bitmapist/json (fetched 2026-08-29T13:12:03.752039+00:00, sha fdc5b1f028e0)
- Data as of 2026-08-30T08:39:29.467469+00:00.